Update README.md

README.md

@@ -11,3 +11,80 @@ license: mit
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+
+---
+
+# Sentiment Analysis with Transformers and Gradio
+
+This script performs sentiment analysis using pre-trained transformer models from the `transformers` library and sets up a user interface using `Gradio` for interaction.
+
+## Installation
+
+### Requirements
+- Python 3.x
+- Required libraries: `transformers`, `datasets`, `gradio`
+
+Install necessary libraries by running:
+
+```bash
+pip install -q transformers datasets gradio
+```
+
+## Usage
+
+1. Clone or download the script.
+2. Ensure Python and required libraries are installed.
+3. Run the script in a Python environment.
+
+The script demonstrates sentiment analysis using a pre-trained model (`avichr/heBERT_sentiment_analysis`) to classify the sentiment of input text into `Negative`, `Neutral`, or `Positive` categories.
+
+### Steps:
+1. Preprocesses the input text by handling placeholders for usernames and links.
+2. Utilizes a pre-trained model (`bert-base-cased`) and the specified sentiment analysis model (`avichr/heBERT_sentiment_analysis`).
+3. Performs sentiment analysis on the provided text, showcasing the confidence scores for each sentiment category.
+
+## Additional Information
+
+- The script demonstrates two methods for sentiment analysis using both PyTorch-based and TensorFlow-based transformer models.
+- The Gradio interface allows users to input text and get a sentiment label prediction based on the pre-trained model.
+
+Please ensure proper environment setup and access to the specified model (`avichr/heBERT_sentiment_analysis`) before running the script 
+
+---
+
+# Sentiment Analysis with Transformers and Gradio
+
+This script performs sentiment analysis using pre-trained transformer models from the `transformers` library and sets up a user interface using `Gradio` for interaction.
+
+## Installation
+
+### Requirements
+- Python 3.x
+- Required libraries: `transformers`, `datasets`, `gradio`
+
+Install necessary libraries by running:
+
+```bash
+pip install -q transformers datasets gradio
+```
+
+## Usage
+
+1. Clone or download the script.
+2. Ensure Python and required libraries are installed.
+3. Run the script in a Python environment.
+
+The script demonstrates sentiment analysis using a pre-trained model (`avichr/heBERT_sentiment_analysis`) to classify the sentiment of input text into `Negative`, `Neutral`, or `Positive` categories.
+
+### Steps:
+1. Preprocesses the input text by handling placeholders for usernames and links.
+2. Utilizes a pre-trained model (`bert-base-cased`) and the specified sentiment analysis model (`avichr/heBERT_sentiment_analysis`).
+3. Performs sentiment analysis on the provided text, showcasing the confidence scores for each sentiment category.
+
+## Additional Information
+
+- The script demonstrates two methods for sentiment analysis using both PyTorch-based and TensorFlow-based transformer models.
+- The Gradio interface allows users to input text and get a sentiment label prediction based on the pre-trained model.
+
+Please ensure proper environment setup and access to the specified model (`avichr/heBERT_sentiment_analysis`) before running